code: def test_scatterplot(df_iris):
      "Test for scatterplot"
  
      # Create Bokeh-Table with DataFrame:
      from bokeh.models import ColumnDataSource
      from bokeh.models.widgets import DataTable, TableColumn
  
      data_table = DataTable(
          columns=[
              TableColumn(field=Ci, title=Ci) for Ci in df_iris.columns
          ],
          source=ColumnDataSource(df_iris.head(10)),
      )
  
      data_table_accessor = DataTable(
          columns=[
              TableColumn(field=Ci, title=Ci) for Ci in df_iris.columns
          ],
          source=ColumnDataSource(df_iris.head(10)),
      )
  
      # Create Scatterplot:
      arguments = dict(
          x="petal length (cm)",
          y="sepal width (cm)",
          category="species",
          title="Iris DataSet Visualization",
          show_figure=False,
      )
  
      p_scatter = df_iris.plot_bokeh(kind="scatter", **arguments)
      p_scatter_accessor = df_iris.plot_bokeh.scatter(**arguments)
  
      p_scatter_pandas_backend = df_iris.plot(
          kind="scatter", **arguments
      )
      p_scatter_accessor_pandas_backend = df_iris.plot.scatter(
          **arguments
      )
  
      # Combine Div and Scatterplot via grid layout:
      output = pandas_bokeh.plot_grid(
          [
              [data_table, p_scatter],
              [
                  data_table_accessor,
                  p_scatter_accessor,
                  p_scatter_pandas_backend,
                  p_scatter_accessor_pandas_backend,
              ],
          ],
          show_plot=False,
          return_html=True,
      )
  
      with open(
          os.path.join(DIRECTORY, "Plots", "Scatterplot.html"), "w"
      ) as f:
          f.write(output)
  
      assert True
  
imports: import os
  import numpy
  import pandas
  import pytest
  import pandas_bokeh
label_desc: Use image node_id 14 for calling a global function with example usage: test_scatterplot(df_iris) without return types